Back to skill

Security audit

Qizheng Oasis

Security checks for vulnerabilities and agentic risk

Overview

The skill is mostly a local simulation/reporting package, but its advertised finance triggers do not match its retail-promotion and public-opinion-crisis behavior, and its dashboard contains an unrelated iframe inspector that can leak page metadata when embedded.

Review before installing. Treat this as a retail promotion and public-opinion crisis simulator, not a stock/fund optimization skill. Avoid embedding the dashboard in untrusted parent pages, do not run auxiliary LLM scripts with sensitive scenarios or real customer data unless you accept sending data to SiliconFlow, and remove or constrain the iframe inspector before use.

Vulnerability Patterns
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (1)

T09 · Insecure Skill Coding Practices

Warning
Location
dashboard/index.html:655
Finding

Unrestricted iframe inspector discloses DOM and form data to untrusted parent origins

Content
View full analysis
50 ? text.substring(0, 50) + "..." : text; } ``` It also collects every attribute from the selected element: ```javascript function getElementAttributes(element) { var attrs = {}; for (var i = 0; i < element.attributes.length; i++) { var attr = element.attributes[i]; attrs[attr.name] = attr.value; } return attrs; } ``` The collected information includes element text, attributes, selector, geometry, complete page URL, path, and timestamp: ```javascript var elementInfo = { tagName: target.tagName.toLowerCase(), rect: { left: rect.left, top: rect.top, right: rect.right, bottom: rect.bottom, width: rect.width, height: rect.height, x: rect.x, y: rect.y }, selector: selector, text: text, attributes: attributes, url: win ...[truncated 6224 chars]
Remediation
View remediation
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Findings (79)

Tp4

High
Category
MCP Tool Poisoning
Confidence
95% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
98% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
98% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
95% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

A conceptually branded OASIS/七政 skill that actually runs parameterized simulations and writes JSON results presents a misleading trust boundary. Users and reviewers may not anticipate persistent storage or the business-domain shift, which increases operational and privacy risk if real data is later fed into the tool.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The blueprint content is materially inconsistent with the declared skill domain: instead of stock/fund optimization, it defines consumer personas and purchase triggers for agricultural group-buy marketing. This kind of domain mismatch is dangerous because it can cause the agent to operate outside user expectations, enabling deceptive repurposing, hidden marketing behavior, or unsafe downstream decisions based on an undeclared objective.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
96% confidence
Finding

The manifest describes a skill about integrating the OASIS three-layer architecture into a 七政 system, with trigger words focused on stocks, A-shares, and funds. This file instead defines consumer-marketing personas for e-commerce promotion, including KOC seeding, bargain-hunting segments, repurchase behavior, and a placeholder role for 刷单占位, which is semantically unrelated to stock or fund analysis.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The file contains a large iframe-inspection/highlighting payload unrelated to the stated stock/fund simulation dashboard. It injects DOM-monitoring behavior, listens for parent-window commands, and exfiltrates iframe element metadata, which is a strong indicator of covert page-inspection capability rather than legitimate dashboard functionality.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The script can capture arbitrary iframe element details including selectors, text, attributes, geometry, URL, and path, then send them to the parent via postMessage('*'). In a financial-themed skill, this unjustified capability could expose sensitive content from embedded pages and enable surveillance of user interactions across contexts.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The file's behavior materially contradicts the declared skill purpose: instead of stock/A-share/fund optimization, it performs blueberry marketing persona generation, simulation, and report writing. Capability mismatch is dangerous because users and platforms may grant trust or execution based on the manifest while the code performs unrelated actions, enabling deceptive repurposing and reducing meaningful consent.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The file's behavior materially diverges from the declared skill purpose: instead of stock/fund optimization, it simulates food-safety public-opinion crises and response operations. This mismatch is dangerous because it can hide undisclosed capabilities from users and reviewers, enabling deceptive deployment of influence-oriented tooling under an unrelated finance label.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

High
Category
Not specified by scanner
Confidence
99% confidence
Finding

The code defines a coordinated crisis-response team with actions such as media contact, narrative control, compensatory messaging, and 'water army' style defensive posting support within a public-opinion simulation. In the context of a mislabeled stock/fund skill, these capabilities suggest undisclosed influence and reputation-management functionality that could be repurposed for manipulative campaigns or deceptive operational planning.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The skill metadata says it is for 股票/A股/基金 optimization, but the code actually simulates social-commerce virality and urgency tactics for a flash-sale agricultural product. This capability mismatch is dangerous because it can bypass user expectations and review controls, and in agent environments it may cause the skill to be invoked in unrelated financial contexts while performing undisclosed persuasion-oriented behavior.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The HTML root sets lang="zh", and the visible skill content is presented entirely in Chinese. Under the policy rule, forcing a specific language without user opt-in or clear justification is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

The documented functionality materially diverges from the declared skill purpose. A skill advertised as stock/fund analysis but actually providing retail promotion and PR-crisis simulation expands scope without user or platform awareness, which can bypass review expectations and cause the skill to be invoked in inappropriate contexts.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The file describes operational PR, legal, customer-service, and reputation-response workflows that are unrelated to the stated stock/fund purpose. This hidden capability increases the chance of deceptive deployment, misuse for influence operations, or unauthorized business decision support outside the reviewed scope.

Content

No source excerpt is available for this finding.

Ae4

Medium
Category
analysis-evasion
Confidence
80% confidence
Finding

Suspicious Unicode normalization or mixed-script content

Content

No source excerpt is available for this finding.

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
87% confidence
Finding

The skill declares no permissions or allowed tool scope, yet the documented behavior and linked scripts indicate access to shell execution, file writes, environment variables, and likely network access. That mismatch weakens containment and informed review, making it easier for the skill to access sensitive resources unexpectedly when installed or invoked.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The trigger list includes very broad terms such as “stock”, “skill”, and “优化”, which can match many unrelated user requests. Over-broad activation increases the chance that the skill runs unexpectedly in contexts where users did not intend to invoke it, potentially exposing data to its file/network behaviors or producing misleading outputs.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The documented trigger phrases are ambiguous and not bounded by scope, so routine requests about simulation, crisis analysis, or generic market discussion may invoke the skill unintentionally. In a skill with reported side effects like file output and possible external/API access, accidental activation meaningfully raises risk.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

This Python file presents its description, report headers, status messages, and recommendations entirely in Chinese, and provides no option for the user to select another language or locale. Under the policy, forcing a specific language without opt-in is a natural-language policy violation unless the locale restriction is explicitly documented and justified.

Content

No source excerpt is available for this finding.